顧客化的資訊提供對於資訊提供者愈來愈重要，傳統專題選粹服務(SDI)因為需要讀者主動的提供資訊，而使得服務的對象小，而且需要讀者參興。使用資料採礦技術能從讀者的借閱記錄中找出讀者的行為，提供顧客化的資訊功能。本研究以中山大學圖書館為資料來源，經由一步步的實作資料採礦的過程，期望對於資料採礦技術應用在圖書館的新書資訊提供上，有具體可行顧客化的資訊服務。
本研究使用讀者概念階層及書目階層，並給定所需要的參數門檻值，找到滿足條件之某類讀者會借閱某類書的規則。為此本研究提出四種演算法，SBSP，SBMP，LatSBMP，MBMP適用於不同情況，並分析其執行效率，對於採礦的過程，本研究採用一般資料採礦的模式，說明實作的每一個步驟。

Customized information service is very important for service provider nowadays. Traditional selective dissemination, as widely discussed in library community requires users’ involvement and only serves a limited amount of users. In this thesis, we propose to employ data mining techniques to discover knowledge in circulation databases so as to provide customized service in library new book recommendation. Our research’s data source is from National Sun Yat-Sen University’s library. We follow a standard data mining procedure and report our experience in this thesis.
Our research uses patron concept hierarchy and book hierarchy with given support threshold and confidence threshold to derived association rules with patron types being antecedent and book types being subsequent. Four algorithms, namely SBSP, SBMP, LatSBMP, MBMP are proposed to facilitate patron and book hierarchy search. Their complexities are compared analytically.

圖表目錄 2
第一章 緒論 4
第二章 研究目的與動機 5
第三章 文獻探討 7
3.1知識發現與資料採礦方法論(Data Mining Methodology) 7
3.2資料採礦技術之相關規則分析(Association rule) 8
3.3圖書館管理 11
第四章 圖書館新書推薦資料採礦進行方式 13
4.1知識發掘與資料採礦過程方法的建構 13
人力資源的指派(Human resource identification). 13
問題的界定(Problem specification). 14
資料的評估(Data prospecting) 15
相關領域知識(Domain knowledge elicitation). 16
確定使用的方法論(Methodology identification) 17
資料的前置處理(Data preprocessing) 26
找出有用的Pattern(Pattern Discovered) 27
導出知識的後序處理(Knowledge post-processing) 34
4.2演算法探討 35
規則的型態分析 53
門檻值的訂定 54
4.3發展實作 56
系統建置 57
第五章 討論 58
第六章 結論 60
參考文獻 61

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